Semantic Data

Getting to know users better with psychographic data reflecting their interests.

Explanations might matter more than the prediction. The more users understand the connections between their recommendations and their personality or lifestyle, the more they engage.

You Can Have the Data that Will Trigger Your Recommendations

We build semantic fingerprints. It means we create profiles that reflect your customers’ content preferences that show through their interactions. And it works because of our human approach.

  • We ease interactions by using natural language to classify content and to explain recommendations.
  • And we give your customers control of what you know about them and the power to change it.

We have the right features for you to build a robust and scalable recommender system.

  • Start by semantically enriching your content to enhance discoverability.
  • And as your customers’ interactions rise, use that information to increase engagement.

Are you ready to find our semantic data features?

content-to-content recommendations

Are You Helping Your Customers Discovering Your Content?

By semantically enriching content we create a content semantic fingerprint.

The content semantic fingerprint is built for each content and eases content-to-content recommendations.

It means that we define keywords based on natural language to classify your content. The keywords are then used to find similarities between content pieces.

You will help your customers finding similar content.

  • You will show your customers a single list of similar content.
  • Or you will present thematic lists of related content pieces categorized into clusters of keywords.

Do you want to know more?